{
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{
"cell_type": "code",
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"metadata": {
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"source": [
"%matplotlib inline\n",
"from datetime import date\n",
"from l1 import l1\n",
"import os\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"from scipy import signal as sp_signal\n",
"from sklearn import ensemble\n",
"import statsmodels.api as sm\n",
"\n",
"plt.style.use('fivethirtyeight')\n",
"\n",
"_DATA_DIR = 'data'\n",
"_FIG_DIR = 'figures'\n",
"\n",
"if not os.path.exists(_FIG_DIR):\n",
" os.makedirs(_FIG_DIR)\n",
"\n",
"_SNP_500_PATH = os.path.join(_DATA_DIR, 'snp500.csv')\n",
"_BEGINNING_DATE = date(2014, 1, 1)\n",
"\n",
"## Matplotlib Variables\n",
"_FIG_SIZE = (16, 12)\n",
"_FIG_FORMAT = 'png'\n",
"_FIG_DPI = 200\n",
"_FIG_LEGEND_LOCATION = 4\n",
"\n",
"_ORIGINAL_SIGNAL_LABEL = 'Original Signal'\n",
"_MEAN_AVERAGE_SIGNAL_LABEL = 'Mean Averaged Signal'\n",
"_MEDIAN_FILTERED_SIGNAL_LABEL = 'Median Filtered Signal'\n",
"_EXPONENTIAL_SMOOTHED_AVERAGE_SIGNAL_LABEL = 'Exponential Moving Averaged Signal'\n",
"_SNP_CYCLE_SIGNAL_LABEL = 'Cycle Signal'\n",
"_SNP_TREND_SIGNAL_LABEL = 'Trend'\n",
"_L1_TREND_SIGNAL_LABEL = '$l_1$ Trend'\n",
"_BAND_PASS_FILTER_LABEL = 'Band-pas filtered'\n",
"\n",
"\n",
"_BUTTERWORTH_FILTER_TITLE = 'Butterworth filter frequency response'\n",
"_BUTTERWORTH_FILTER_XLABEL = 'Frequency [radians / second]'\n",
"_BUTTERWORTH_FILTER_YLABEL = 'Amplitude [dB]'\n",
"\n",
"_MEAN_AVERAGE_SIGNAL_TITLE_TEMPLATE = 'Mean Average signal with window = {}'.format\n",
"_MEDIAN_FILTER_SIGNAL_TITLE_TEMPLATE = 'Median Filtered signal with window = {}'.format\n",
"_EXPONENTIAL_SMOOTHING_TITLE_TEMPLATE = 'Exponential Smoothed signal with span = {}'.format\n",
"_HODRICK_PRESSCOTT_TITLE_TEMPLATE = 'Trend and Cycle Signal with smoothing parameter: {}'.format\n",
"_L1_TITLE_TEMPLATE = '$l_1$ Trend Signal with regularizer: {}'.format\n",
"_BAND_PASS_TITLE_TEMPLATE = 'Band-pass order: {}, low - high cutoff frequency: {} - {}'.format"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"### Data Explanation\n",
"- The S&P 500, or the Standard & Poor's 500, is an American stock market index based on the market capitalizations of 500 large companies having common stock listed on the NYSE or NASDAQ. \n",
"- The S&P 500 index components and their weightings are determined by S&P Dow Jones Indices. \n",
"- It differs from other U.S. stock market indices, such as the Dow Jones Industrial Average or the Nasdaq Composite index, because of its diverse constituency and weighting methodology. \n",
"- It is one of the most commonly followed equity indices, and many consider it one of the best representations of the U.S. stock market, and a bellwether for the U.S. economy. \n",
"- The National Bureau of Economic Research has classified common stocks as a leading indicator of __business cycles__.\n",
"\n",
"Reference: http://www.albany.edu/cer/bc/bc_essays.html"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def _file_format(string_):\n",
" string_ = string_.replace('-', '_').replace(' ', '_').replace('$', '')\n",
" string_ += '.' + _FIG_FORMAT\n",
" return string_"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"df = pd.read_csv(_SNP_500_PATH, parse_dates=['Date'])\n",
"df = df.sort(['Date'])\n",
"df = df[df.Date > _BEGINNING_DATE]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
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